Building Smart Agents with Vertex AI Agent Builder & RAG Training Course

Introduction to Agent Builder and RAG

• Exploring the capabilities of Agent Builder
• Core principles of RAG and appropriate application scenarios
• Real-world use cases and success stories

Environment Configuration

• Setting up the Vertex AI workspace
• Linking search and vector storage systems
• Practical lab: Preparing the working environment

Designing Grounded Agent Workflows

• Establishing agent objectives and dialogue flows
• Aligning data sources with retrieval strategies
• Practical lab: Constructing a conversation flow

Implementing RAG Pipelines

• Indexing documents and managing embeddings
• Utilizing retriever and re-ranker patterns
• Practical lab: Building a RAG pipeline

Integrations and Enterprise Data

• Establishing secure connections to internal systems
• Managing data governance and access permissions
• Practical lab: Linking enterprise data sources

Testing, Evaluation, and Iteration

• Conducting prompt testing and measuring performance metrics
• Employing user simulation and validation techniques
• Practical lab: Assessing and optimizing agent behavior

Deployment, Monitoring, and Maintenance

• Reviewing deployment options and scalability factors
• Tracking performance, relevance, and drift over time
• Developing operational guides for updates and rollback procedures

Summary and Future Directions